Dataset: Divvy 2019

About this Dataset

Divvy 2019

Overview

This dataset is based on a bike renting company called Cyclistic which takes place in Chicago , their director of marketing believes the company’s future success depends on maximizing the number of annual memberships . Therefore, Our team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, Our team will design a new marketing strategy to convert casual riders into annual members

Content

the data after further inspections shows a bit of unexplained data where some rides too months which didn't make sense so we added a criteria of 120 mins maximum rides so we get a real understanding of the data , our goal is to clean , organize , filter & sort so we can make observations on the data , i acquired the data from : https://ride.divvybikes.com/system-data ,which is an open source data with the license agreement :https://ride.divvybikes.com/data-license-agreement , this data set takes place in 2019 whole year .

Acknowledgements

can't disregard the help of the people around me makes it much easier to have other insights regarding the points of view and other ways to tackle the problem on hand .

Tables

Divvy Trips 2019 Q4

@kaggle.moazmohamedhassan_divvy_2019.divvy_trips_2019_q4

19.43 MB
704054 rows
12 columns


CREATE TABLE divvy_trips_2019_q4 (
  "trip_id" BIGINT,
  "start_time" TIMESTAMP,
  "end_time" TIMESTAMP,
  "bikeid" BIGINT,
  "tripduration" DOUBLE,
  "from_station_id" BIGINT,
  "from_station_name" VARCHAR,
  "to_station_id" BIGINT,
  "to_station_name" VARCHAR,
  "usertype" VARCHAR,
  "gender" VARCHAR,
  "birthyear" DOUBLE
);

Divvy Trips 2019 Q2

@kaggle.moazmohamedhassan_divvy_2019.divvy_trips_2019_q2

29.95 MB
1108163 rows
12 columns


CREATE TABLE divvy_trips_2019_q2 (
  "n_01_rental_details_rental_id" BIGINT,
  "n_01_rental_details_local_start_time" TIMESTAMP,
  "n_01_rental_details_local_end_time" TIMESTAMP,
  "n_01_rental_details_bike_id" BIGINT,
  "n_01_rental_details_duration_in_seconds_uncapped" DOUBLE,
  "n_03_rental_start_station_id" BIGINT,
  "n_03_rental_start_station_name" VARCHAR,
  "n_02_rental_end_station_id" BIGINT,
  "n_02_rental_end_station_name" VARCHAR,
  "user_type" VARCHAR,
  "member_gender" VARCHAR,
  "n_05_member_details_member_birthday_year" DOUBLE
);

Divvy Trips 2019 Q3

@kaggle.moazmohamedhassan_divvy_2019.divvy_trips_2019_q3

43.7 MB
1640718 rows
12 columns


CREATE TABLE divvy_trips_2019_q3 (
  "trip_id" BIGINT,
  "start_time" TIMESTAMP,
  "end_time" TIMESTAMP,
  "bikeid" BIGINT,
  "tripduration" DOUBLE,
  "from_station_id" BIGINT,
  "from_station_name" VARCHAR,
  "to_station_id" BIGINT,
  "to_station_name" VARCHAR,
  "usertype" VARCHAR,
  "gender" VARCHAR,
  "birthyear" DOUBLE
);

Divvy Trips 2019 Q1

@kaggle.moazmohamedhassan_divvy_2019.divvy_trips_2019_q1

10.15 MB
365069 rows
12 columns


CREATE TABLE divvy_trips_2019_q1 (
  "trip_id" BIGINT,
  "start_time" TIMESTAMP,
  "end_time" TIMESTAMP,
  "bikeid" BIGINT,
  "tripduration" DOUBLE,
  "from_station_id" BIGINT,
  "from_station_name" VARCHAR,
  "to_station_id" BIGINT,
  "to_station_name" VARCHAR,
  "usertype" VARCHAR,
  "gender" VARCHAR,
  "birthyear" DOUBLE
);